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Multi-sensor optimal data fusion for INS/GPS/SAR integrated navigation system
Authors:Shesheng Gao  Yongmin Zhong  Xueyuan Zhang  Bijan Shirinzadeh
Institution:aSchool of Automation, Northwestern Polytechnical University, Xi'an 710072, China;bDepartment of Mechanical Engineering, Curtin University of Technology, Australia;cDepartment of Mechanical and Aerospace Engineering, Monash University, Australia
Abstract:INS/GPS/SAR integrated navigation system represents the trend of next generation navigation systems with the high performance of independence, high precision and reliability. This paper presents a new multi-sensor data fusion methodology for INS/GPS/SAR integrated navigation systems. This methodology combines local decentralized fusion with global optimal fusion to enhance the accuracy and reliability of integrated navigation systems. A decentralized estimation fusion method is established for individual integrations of GPS and SAR into INS to obtain the local optimal state estimations in a parallel manner. A global optimal estimation fusion theory is studied to fuse the local optimal estimations for generating the global optimal state estimation of INS/GPS/SAR integrated navigation systems. The global data fusion features a method of variance upper finiteness and a method of variance upper bound to ensure that the global optimal state estimation can be achieved under a general condition. Experimental results demonstrate that INS/GPS/SAR integrated navigation systems achieved by using the proposed methodology have a better performance than INS/GPS integrated systems.
Keywords:Integrated navigation system  Data fusion  Decentralized fusion and global optimal fusion
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